Instrukcemi řízené celulární automaty

The thesis focuses on a new concept of cellular automata control based on instructions. The instruction can be understood as a rule that checks the states of cells in pre-defined areas in the cellular neighbourhood. If a given condition is satisfied, the state of the central cell is changed according to the definition of the instruction. Because it's possible to perform more instructions in one computational step, their sequence can be understood as a form of a short program. This concept can be extended with simple operations applied to the instruction's prescription during interpretation of the instructions - an example of such operation can be row shift or column shift. An advantage of the instruction-based approach lies in the search space reduction. In comparison with the table-based approach, it isn't necessary to search all the possible configurations of the cellular neighbouhood, but only several areas determined by the instructions. While the groups of the inspected cells in the cellular neighbourhood are designed manually on the basis of the analysis of the solved task, their sequence in the chromosome is optimized by genetic algorithm. The capability of the proposed method of cellular automata control is studied on these benchmark tasks - majority, synchronization, self-organization and the design of combinational circuits.

Cellular automata, evolutionary algorithm, genetic algorithm, majority task, synchronization task, self-organization task.